TYP: more misc annotations

pandas/_config/config.py

@@ -75,6 +75,7 @@
     from collections.abc import (
         Generator,
         Iterable,
+        Sequence,
     )
 
 
@@ -853,7 +854,7 @@ def inner(x) -> None:
     return inner
 
 
-def is_instance_factory(_type) -> Callable[[Any], None]:
+def is_instance_factory(_type: type | tuple[type, ...]) -> Callable[[Any], None]:
     """
 
     Parameters
@@ -866,8 +867,7 @@ def is_instance_factory(_type) -> Callable[[Any], None]:
                 ValueError if x is not an instance of `_type`
 
     """
-    if isinstance(_type, (tuple, list)):
-        _type = tuple(_type)
+    if isinstance(_type, tuple):
         type_repr = "|".join(map(str, _type))
     else:
         type_repr = f"'{_type}'"
@@ -879,7 +879,7 @@ def inner(x) -> None:
     return inner
 
 
-def is_one_of_factory(legal_values) -> Callable[[Any], None]:
+def is_one_of_factory(legal_values: Sequence) -> Callable[[Any], None]:
     callables = [c for c in legal_values if callable(c)]
     legal_values = [c for c in legal_values if not callable(c)]
 
@@ -930,7 +930,7 @@ def is_nonnegative_int(value: object) -> None:
 is_text = is_instance_factory((str, bytes))
 
 
-def is_callable(obj) -> bool:
+def is_callable(obj: object) -> bool:
     """
 
     Parameters

pandas/core/arrays/period.py

@@ -759,7 +759,7 @@ def asfreq(self, freq=None, how: str = "E") -> Self:
     # ------------------------------------------------------------------
     # Rendering Methods
 
-    def _formatter(self, boxed: bool = False):
+    def _formatter(self, boxed: bool = False) -> Callable[[object], str]:
         if boxed:
             return str
         return "'{}'".format

pandas/core/arrays/timedeltas.py

@@ -1080,7 +1080,7 @@ def sequence_to_td64ns(
     return data, inferred_freq
 
 
-def _ints_to_td64ns(data, unit: str = "ns"):
+def _ints_to_td64ns(data, unit: str = "ns") -> tuple[np.ndarray, bool]:
     """
     Convert an ndarray with integer-dtype to timedelta64[ns] dtype, treating
     the integers as multiples of the given timedelta unit.
@@ -1120,7 +1120,9 @@ def _ints_to_td64ns(data, unit: str = "ns"):
     return data, copy_made
 
 
-def _objects_to_td64ns(data, unit=None, errors: DateTimeErrorChoices = "raise"):
+def _objects_to_td64ns(
+    data, unit=None, errors: DateTimeErrorChoices = "raise"
+) -> np.ndarray:
     """
     Convert a object-dtyped or string-dtyped array into an
     timedelta64[ns]-dtyped array.

pandas/core/config_init.py

@@ -329,7 +329,7 @@ def is_terminal() -> bool:
         "min_rows",
         10,
         pc_min_rows_doc,
-        validator=is_instance_factory([type(None), int]),
+        validator=is_instance_factory((type(None), int)),
     )
     cf.register_option("max_categories", 8, pc_max_categories_doc, validator=is_int)
 
@@ -369,7 +369,7 @@ def is_terminal() -> bool:
     cf.register_option("chop_threshold", None, pc_chop_threshold_doc)
     cf.register_option("max_seq_items", 100, pc_max_seq_items)
     cf.register_option(
-        "width", 80, pc_width_doc, validator=is_instance_factory([type(None), int])
+        "width", 80, pc_width_doc, validator=is_instance_factory((type(None), int))
     )
     cf.register_option(
         "memory_usage",
@@ -850,14 +850,14 @@ def register_converter_cb(key) -> None:
         "format.thousands",
         None,
         styler_thousands,
-        validator=is_instance_factory([type(None), str]),
+        validator=is_instance_factory((type(None), str)),
     )
 
     cf.register_option(
         "format.na_rep",
         None,
         styler_na_rep,
-        validator=is_instance_factory([type(None), str]),
+        validator=is_instance_factory((type(None), str)),
     )
 
     cf.register_option(
@@ -867,11 +867,15 @@ def register_converter_cb(key) -> None:
         validator=is_one_of_factory([None, "html", "latex", "latex-math"]),
     )
 
+    # error: Argument 1 to "is_instance_factory" has incompatible type "tuple[
+    # ..., <typing special form>, ...]"; expected "type | tuple[type, ...]"
     cf.register_option(
         "format.formatter",
         None,
         styler_formatter,
-        validator=is_instance_factory([type(None), dict, Callable, str]),
+        validator=is_instance_factory(
+            (type(None), dict, Callable, str)  # type: ignore[arg-type]
+        ),
     )
 
     cf.register_option("html.mathjax", True, styler_mathjax, validator=is_bool)
@@ -898,7 +902,7 @@ def register_converter_cb(key) -> None:
         "latex.environment",
         None,
         styler_environment,
-        validator=is_instance_factory([type(None), str]),
+        validator=is_instance_factory((type(None), str)),
     )
 
 

pandas/core/dtypes/missing.py

@@ -557,11 +557,13 @@ def _array_equivalent_float(left: np.ndarray, right: np.ndarray) -> bool:
     return bool(((left == right) | (np.isnan(left) & np.isnan(right))).all())
 
 
-def _array_equivalent_datetimelike(left: np.ndarray, right: np.ndarray):
+def _array_equivalent_datetimelike(left: np.ndarray, right: np.ndarray) -> bool:
     return np.array_equal(left.view("i8"), right.view("i8"))
 
 
-def _array_equivalent_object(left: np.ndarray, right: np.ndarray, strict_nan: bool):
+def _array_equivalent_object(
+    left: np.ndarray, right: np.ndarray, strict_nan: bool
+) -> bool:
     left = ensure_object(left)
     right = ensure_object(right)
 

pandas/core/frame.py

@@ -233,6 +233,7 @@
         IndexLabel,
         JoinValidate,
         Level,
+        ListLike,
         MergeHow,
         MergeValidate,
         MutableMappingT,
@@ -5349,11 +5350,11 @@ def reindex(
     @overload
     def drop(
         self,
-        labels: IndexLabel = ...,
+        labels: IndexLabel | ListLike = ...,
         *,
         axis: Axis = ...,
-        index: IndexLabel = ...,
-        columns: IndexLabel = ...,
+        index: IndexLabel | ListLike = ...,
+        columns: IndexLabel | ListLike = ...,
         level: Level = ...,
         inplace: Literal[True],
         errors: IgnoreRaise = ...,
@@ -5363,11 +5364,11 @@ def drop(
     @overload
     def drop(
         self,
-        labels: IndexLabel = ...,
+        labels: IndexLabel | ListLike = ...,
         *,
         axis: Axis = ...,
-        index: IndexLabel = ...,
-        columns: IndexLabel = ...,
+        index: IndexLabel | ListLike = ...,
+        columns: IndexLabel | ListLike = ...,
         level: Level = ...,
         inplace: Literal[False] = ...,
         errors: IgnoreRaise = ...,
@@ -5377,11 +5378,11 @@ def drop(
     @overload
     def drop(
         self,
-        labels: IndexLabel = ...,
+        labels: IndexLabel | ListLike = ...,
         *,
         axis: Axis = ...,
-        index: IndexLabel = ...,
-        columns: IndexLabel = ...,
+        index: IndexLabel | ListLike = ...,
+        columns: IndexLabel | ListLike = ...,
         level: Level = ...,
         inplace: bool = ...,
         errors: IgnoreRaise = ...,
@@ -5390,11 +5391,11 @@ def drop(
 
     def drop(
         self,
-        labels: IndexLabel | None = None,
+        labels: IndexLabel | ListLike = None,
         *,
         axis: Axis = 0,
-        index: IndexLabel | None = None,
-        columns: IndexLabel | None = None,
+        index: IndexLabel | ListLike = None,
+        columns: IndexLabel | ListLike = None,
         level: Level | None = None,
         inplace: bool = False,
         errors: IgnoreRaise = "raise",

pandas/core/generic.py

@@ -65,6 +65,7 @@
     IntervalClosedType,
     JSONSerializable,
     Level,
+    ListLike,
     Manager,
     NaPosition,
     NDFrameT,
@@ -4709,11 +4710,11 @@ def reindex_like(
     @overload
     def drop(
         self,
-        labels: IndexLabel = ...,
+        labels: IndexLabel | ListLike = ...,
         *,
         axis: Axis = ...,
-        index: IndexLabel = ...,
-        columns: IndexLabel = ...,
+        index: IndexLabel | ListLike = ...,
+        columns: IndexLabel | ListLike = ...,
         level: Level | None = ...,
         inplace: Literal[True],
         errors: IgnoreRaise = ...,
@@ -4723,11 +4724,11 @@ def drop(
     @overload
     def drop(
         self,
-        labels: IndexLabel = ...,
+        labels: IndexLabel | ListLike = ...,
         *,
         axis: Axis = ...,
-        index: IndexLabel = ...,
-        columns: IndexLabel = ...,
+        index: IndexLabel | ListLike = ...,
+        columns: IndexLabel | ListLike = ...,
         level: Level | None = ...,
         inplace: Literal[False] = ...,
         errors: IgnoreRaise = ...,
@@ -4737,11 +4738,11 @@ def drop(
     @overload
     def drop(
         self,
-        labels: IndexLabel = ...,
+        labels: IndexLabel | ListLike = ...,
         *,
         axis: Axis = ...,
-        index: IndexLabel = ...,
-        columns: IndexLabel = ...,
+        index: IndexLabel | ListLike = ...,
+        columns: IndexLabel | ListLike = ...,
         level: Level | None = ...,
         inplace: bool_t = ...,
         errors: IgnoreRaise = ...,
@@ -4750,11 +4751,11 @@ def drop(
 
     def drop(
         self,
-        labels: IndexLabel | None = None,
+        labels: IndexLabel | ListLike = None,
         *,
         axis: Axis = 0,
-        index: IndexLabel | None = None,
-        columns: IndexLabel | None = None,
+        index: IndexLabel | ListLike = None,
+        columns: IndexLabel | ListLike = None,
         level: Level | None = None,
         inplace: bool_t = False,
         errors: IgnoreRaise = "raise",

pandas/core/methods/selectn.py

@@ -10,6 +10,7 @@
 )
 from typing import (
     TYPE_CHECKING,
+    Generic,
     cast,
     final,
 )
@@ -32,32 +33,41 @@
     from pandas._typing import (
         DtypeObj,
         IndexLabel,
+        NDFrameT,
     )
 
     from pandas import (
         DataFrame,
         Series,
     )
+else:
+    # Generic[...] requires a non-str, provide it with a plain TypeVar at
+    # runtime to avoid circular imports
+    from pandas._typing import T
 
+    NDFrameT = T
+    DataFrame = T
+    Series = T
 
-class SelectN:
-    def __init__(self, obj, n: int, keep: str) -> None:
+
+class SelectN(Generic[NDFrameT]):
+    def __init__(self, obj: NDFrameT, n: int, keep: str) -> None:
         self.obj = obj
         self.n = n
         self.keep = keep
 
         if self.keep not in ("first", "last", "all"):
             raise ValueError('keep must be either "first", "last" or "all"')
 
-    def compute(self, method: str) -> DataFrame | Series:
+    def compute(self, method: str) -> NDFrameT:
         raise NotImplementedError
 
     @final
-    def nlargest(self):
+    def nlargest(self) -> NDFrameT:
         return self.compute("nlargest")
 
     @final
-    def nsmallest(self):
+    def nsmallest(self) -> NDFrameT:
         return self.compute("nsmallest")
 
     @final
@@ -72,7 +82,7 @@ def is_valid_dtype_n_method(dtype: DtypeObj) -> bool:
         return needs_i8_conversion(dtype)
 
 
-class SelectNSeries(SelectN):
+class SelectNSeries(SelectN[Series]):
     """
     Implement n largest/smallest for Series
 
@@ -163,7 +173,7 @@ def compute(self, method: str) -> Series:
         return concat([dropped.iloc[inds], nan_index]).iloc[:findex]
 
 
-class SelectNFrame(SelectN):
+class SelectNFrame(SelectN[DataFrame]):
     """
     Implement n largest/smallest for DataFrame
 

pandas/core/missing.py

@@ -960,14 +960,11 @@ def _pad_2d(
     values: np.ndarray,
     limit: int | None = None,
     mask: npt.NDArray[np.bool_] | None = None,
-):
+) -> tuple[np.ndarray, npt.NDArray[np.bool_]]:
     mask = _fillna_prep(values, mask)
 
     if values.size:
         algos.pad_2d_inplace(values, mask, limit=limit)
-    else:
-        # for test coverage
-        pass
     return values, mask